Molecular ecology of microbiomes in the wild: Common pitfalls, methodological advances and future directions.

The study of microbiomes across organisms and environments has become a prominent focus in molecular ecology. This perspective article explores common challenges, methodological advancements, and future directions in the field. Key research areas include understanding the drivers of microbiome community assembly, linking microbiome composition to host genetics, exploring microbial functions, transience and spatial partitioning, and disentangling non-bacterial components of the microbiome. Methodological advancements, such as quantifying absolute abundances, sequencing complete genomes, and utilizing novel statistical approaches, are also useful tools for understanding complex microbial diversity patterns. Our aims are to encourage robust practices in microbiome studies and inspire researchers to explore the next frontier of this rapidly changing field.

A De Novo Whole Genome Assembly and Annotation of Parelaphostrongylus tenuis.

Parelaphostrongylus tenuis causes ungulate morbidity and mortality in eastern and central North America, but no reference genome sequence exists to facilitate research. Here, we present a P. tenuis genome assembly and annotation, generated with PacBio and Illumina technologies. The assembly is 491 Mbp, with 7285 scaffolds and 185 kb N50.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza.

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

The spectral underpinnings of pathogen spread on animal networks.

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

Positive associations matter: Microbial relationships drive tick microbiome composition.

Untangling how factors such as environment, host, associations among bacterial species and dispersal predict microbial composition is a fundamental challenge. In this study, we use complementary machine-learning approaches to quantify the relative role of these factors in shaping microbiome variation of the blacklegged tick Ixodes scapularis. I. scapularis is the most important vector for Borrelia burgdorferi (the causative agent for Lyme disease) in the U.S. as well as a range of other important zoonotic pathogens. Yet the relative role of the interactions between pathogens and symbionts compared to other ecological forces is unknown. We found that positive associations between microbes where the occurrence of one microbe increases the probability of observing another, including between both pathogens and symbionts, was by far the most important factor shaping the tick microbiome. Microclimate and host factors played an important role for a subset of the tick microbiome including Borrelia (Borreliella) and Ralstonia, but for the majority of microbes, environmental and host variables were poor predictors at a regional scale. This study provides new hypotheses on how pathogens and symbionts might interact within tick species, as well as valuable predictions for how some taxa may respond to changing climate.

Automated Analysis of PD1 and PDL1 Expression in Lymph Nodes and the Microenvironment of Transmissible Tumors in Tasmanian Devils.

The wild Tasmanian devil (Sarcophilus harrisii) population has suffered a devastating decline due to two clonal transmissible cancers. The first devil facial tumor 1 (DFT1) was observed in 1996, followed by a second genetically distinct transmissible tumor, the devil facial tumor 2 (DFT2), in 2014. DFT1/2 frequently metastasize, with lymph nodes being common metastatic sites. MHC-I downregulation by DFT1 cells is a primary means of evading allograft immunity aimed at polymorphic MHC-I proteins. DFT2 cells constitutively express MHC-I, and MHC-I is upregulated on DFT1/2 cells by interferon gamma, suggesting other immune evasion mechanisms may contribute to overcoming allograft and anti-tumor immunity. Human clinical trials have demonstrated PD1/PDL1 blockade effectively treats patients showing increased expression of PD1 in tumor draining lymph nodes, and PDL1 on peritumoral immune cells and tumor cells. The effects of DFT1/2 on systemic immunity remain largely uncharacterized. This study applied the open-access software QuPath to develop a semiautomated pipeline for whole slide analysis of stained tissue sections to quantify PD1/PDL1 expression in devil lymph nodes. The QuPath protocol provided strong correlations to manual counting. PD-1 expression was approximately 10-fold higher than PD-L1 expression in lymph nodes and was primarily expressed in germinal centers, whereas PD-L1 expression was more widely distributed throughout the lymph nodes. The density of PD1 positive cells was increased in lymph nodes containing DFT2 metastases, compared to DFT1. This suggests PD1/PDL1 exploitation may contribute to the poorly immunogenic nature of transmissible tumors in some devils and could be targeted in therapeutic or prophylactic treatments.Abbreviations: PD1: programmed cell death protein 1; PDL1: programmed death ligand 1; DFT1: devil facial tumor 1; DFT2: devil facial tumor 2; DFTD: devil facial tumor disease; MCC: Matthew's correlation coefficient; DAB: diaminobenzidine; ROI: region of interest.

Parasites as conservation tools.

Parasite success typically depends on a close relationship with one or more hosts; therefore, attributes of parasitic infection have the potential to provide indirect details of host natural history and are biologically relevant to animal conservation. Characterization of parasite infections has been useful in delineating host populations and has served as a proxy for assessment of environmental quality. In other cases, the utility of parasites is just being explored, for example, as indicators of host connectivity. Innovative studies of parasite biology can provide information to manage major conservation threats by using parasite assemblage, prevalence, or genetic data to provide insights into the host. Overexploitation, habitat loss and fragmentation, invasive species, and climate change are major threats to animal conservation, and all of these can be informed by parasites.

Los Parásitos como Herramienta de Conservación Resumen El éxito de los parásitos depende típicamente de la relación cercana con uno o más hospederos; por lo tanto, las características de la infección parasitaria tienen potencial para proporcionar detalles indirectos de la historia natural del hospedero y son biológicamente relevantes para la conservación animal. La caracterización de las infecciones parasitarias ha sido útil para definir a las poblaciones hospederas y ha servido como sustituto para la evaluación de la calidad ambiental. Los estudios innovadores de la biología de parásitos pueden proporcionar información para manejar las principales amenazas a la conservación mediante la información proporcionada por el conjunto de parásitos, su prevalencia o genética que proporciona conocimiento sobre el hospedero. La sobreexplotación, la pérdida del hábitat y la fragmentación, las especies invasoras y el cambio climático son las principales amenazas para la conservación animal y a todas pueden ser informadas mediante los parásitos.

Interspecies bacterial communication produces a delicate balance between Vibrio cholerae and the chironomid egg mass microbiome.

The evolution of antimicrobial resistance in bacterial pathogens is considered by the World Health Organization to be one of the ten most concerning public health threats facing humanity (World Health Organization, 2020). Bacterial diseases previously controllable by antibiotics are resurging and treatment options are dwindling. Cholera is one such disease. Human pathogenic strains of Vibrio cholerae cause as many as 4 million cases of disease resulting in over 100,000 deaths each year (Ali et al. 2015) and multidrug-resistant V. cholerae is now established where pandemic cholera persists. Vibrio cholerae is fundamentally an aquatic species thriving in brackish and estuarial waters. Its environmental prevalence, together with both extracellular and intracellular infection of alternative arthropod and mollusc hosts, produces a highly complex ecological milieu that is not well understood. With the absence of reliable antibiotic-based treatment options, it is necessary to build a better understanding of V. cholerae biology and ecology in order to develop alternative methods for risk modelling and disease control. In this issue of Molecular Ecology, authors Sela, Hammer, and Halpern experimentally investigated a mechanism by which V. cholerae pathogenicity is affected by interspecies quorum sensing involving an array of bacterial species from the microbiome of an alternative arthropod host, the egg mass of a chironomid midge (Diptera:Chironomidae) (Sela et al. 2020). Quorum sensing is a mechanism whereby bacteria communicate with each other using autoinducers and is known to be important, for example, in shaping virulence in a variety of pathogenic bacteria. The innovative methodologies they used, both in molecular and protein biology and reductive investigative microbiomics, are helping to develop the tools needed for understanding this understudied ecological system and fighting cholera in a post-antibiotic world.

Environment, vector, or host? Using machine learning to untangle the mechanisms driving arbovirus outbreaks.

Climatic, landscape, and host features are critical components in shaping outbreaks of vector-borne diseases. However, the relationship between the outbreaks of vector-borne pathogens and their environmental drivers is typically complicated, nonlinear, and may vary by taxonomic units below the species level (e.g., strain or serotype). Here, we aim to untangle how these complex forces shape the risk of outbreaks of Bluetongue virus (BTV); a vector-borne pathogen that is continuously emerging and re-emerging across Europe, with severe economic implications. We tested if the ecological predictors of BTV outbreak risk were serotype-specific by examining the most prevalent serotypes recorded in Europe (1, 4, and 8). We used a robust machine learning (ML) pipeline and 23 relevant environmental features to fit predictive models to 24,245 outbreaks reported in 25 European countries between 2000 and 2019. Our ML models demonstrated high predictive performance for all BTV serotypes (accuracies > 0.87) and revealed strong nonlinear relationships between BTV outbreak risk and environmental and host features. Serotype-specific analysis suggests, however, that each of the major serotypes (1, 4, and 8) had a unique outbreak risk profile. For example, temperature and midge abundance were as the most important characteristics shaping serotype 1, whereas for serotype 4 goat density and temperature were more important. We were also able to identify strong interactive effects between environmental and host characteristics that were also serotype specific. Our ML pipeline was able to reveal more in-depth insights into the complex epidemiology of BTVs and can guide policymakers in intervention strategies to help reduce the economic implications and social cost of this important pathogen.

Group density, disease, and season shape territory size and overlap of social carnivores.

The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We further aim to explore the mechanisms by which disease perturbations could cause changes in spatial organization. Here we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We use network analysis to describe spatial organization and connectivity of social groups. We then examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups and shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may have altered lion spatial organization, highlighting the importance of including infectious disease epizootics in studies of behavioural and movement ecology. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions and pathogen infections.

Cross-species transmission and evolutionary dynamics of canine distemper virus during a spillover in African lions of Serengeti National Park.

The outcome of pathogen spillover from a reservoir to a novel host population can range from a "dead-end" when there is no onward transmission in the recipient population, to epidemic spread and even establishment in new hosts. Understanding the evolutionary epidemiology of spillover events leading to discrete outcomes in novel hosts is key to predicting risk and can lead to a better understanding of the mechanisms of emergence. Here we use a Bayesian phylodynamic approach to examine cross-species transmission and evolutionary dynamics during a canine distemper virus (CDV) spillover event causing clinical disease and population decline in an African lion population (Panthera leo) in the Serengeti Ecological Region between 1993 and 1994. Using 21 near-complete viral genomes from four species we found that this large-scale outbreak was likely  ignited by a single cross-species spillover event from a canid reservoir to noncanid hosts <1 year before disease detection and explosive spread of CDV in lions. Cross-species transmission from other noncanid species probably fuelled the high prevalence of CDV across spatially structured lion prides. Multiple lines of evidence suggest that spotted hyenas (Crocuta crocuta) could have acted as the proximate source of CDV exposure in lions. We report 13 nucleotide substitutions segregating CDV strains found in canids and noncanids. Our results are consistent with the hypothesis that virus evolution played a role in CDV emergence in noncanid hosts following spillover during the outbreak, suggest that host barriers to clinical infection can limit outcomes of CDV spillover in novel host species.

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition.

Microbial communities are increasingly recognized as crucial for animal health. However, our understanding of how microbial communities are structured across wildlife populations is poor. Mechanisms such as interspecific associations are important in structuring free-living communities, but we still lack an understanding of how important interspecific associations are in structuring gut microbial communities in comparison with other factors such as host characteristics or spatial proximity of hosts. Here, we ask how gut microbial communities are structured in a population of North American moose Alces alces. We identify key microbial interspecific associations within the moose gut and quantify how important they are relative to key host characteristics, such as body condition, for predicting microbial community composition. We sampled gut microbial communities from 55 moose in a population experiencing decline due to a myriad of factors, including pathogens and malnutrition. We examined microbial community dynamics in this population utilizing novel graphical network models that can explicitly incorporate spatial information. We found that interspecific associations were the most important mechanism structuring gut microbial communities in moose and detected both positive and negative associations. Models only accounting for associations between microbes had higher predictive value compared to models including moose sex, evidence of previous pathogen exposure or body condition. Adding spatial information on moose location further strengthened our model and allowed us to predict microbe occurrences with ~90% accuracy. Collectively, our results suggest that microbial interspecific associations coupled with host spatial proximity are vital in shaping gut microbial communities in a large herbivore. In this case, previous pathogen exposure and moose body condition were not as important in predicting gut microbial community composition. The approach applied here can be used to quantify interspecific associations and gain a more nuanced understanding of the spatial and host factors shaping microbial communities in non-model hosts.

Endemic infection can shape exposure to novel pathogens: Pathogen co-occurrence networks in the Serengeti lions.

Pathogens are embedded in a complex network of microparasites that can collectively or individually alter disease dynamics and outcomes. Endemic pathogens that infect an individual in the first years of life, for example, can either facilitate or compete with subsequent pathogens thereby exacerbating or ameliorating morbidity and mortality. Pathogen associations are ubiquitous but poorly understood, particularly in wild populations. We report here on 10 years of serological and molecular data in African lions, leveraging comprehensive demographic and behavioural data to test if endemic pathogens shape subsequent infection by epidemic pathogens. We combine network and community ecology approaches to assess broad network structure and characterise associations between pathogens across spatial and temporal scales. We found significant non-random structure in the lion-pathogen co-occurrence network and identified both positive and negative associations between endemic and epidemic pathogens. Our results provide novel insights on the complex associations underlying pathogen co-occurrence networks.

Urbanization impacts apex predator gene flow but not genetic diversity across an urban-rural divide.

Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were genotyped using double-digest, restriction site-associated DNA sequencing (ddRADseq). We investigated patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, genome-scale markers to document subtle impacts of urbanization on a wide-ranging carnivore living near a large urban center.

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure.

Predicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data are available on a subset of individuals and nonlinear relationships between variables are common. Here we provide a guide to the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex nonlinear relationships with minimal statistical assumptions from ecological data with missing data. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus. Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualize strong nonlinear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years. When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure that are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.

The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise.

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication," 2) "Methodological and analytical advancements," 3) "Translation into practice," 4) "Integrating landscape ecology and genomics," and 5) "Emerging new questions." Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

Mitochondrial genome sequencing reveals potential origins of the scabies mite Sarcoptes scabiei infesting two iconic Australian marsupials.

BACKGROUND: Debilitating skin infestations caused by the mite, Sarcoptes scabiei, have a profound impact on human and animal health globally. In Australia, this impact is evident across different segments of Australian society, with a growing recognition that it can contribute to rapid declines of native Australian marsupials. Cross-host transmission has been suggested to play a significant role in the epidemiology and origin of mite infestations in different species but a chronic lack of genetic resources has made further inferences difficult. To investigate the origins and molecular epidemiology of S. scabiei in Australian wildlife, we sequenced the mitochondrial genomes of S. scabiei from diseased wombats (Vombatus ursinus) and koalas (Phascolarctos cinereus) spanning New South Wales, Victoria and Tasmania, and compared them with the recently sequenced mitochondrial genome sequences of S. scabiei from humans. RESULTS: We found unique S. scabiei haplotypes among individual wombat and koala hosts with high sequence similarity (99.1% - 100%). Phylogenetic analysis of near full-length mitochondrial genomes revealed three clades of S. scabiei (one human and two marsupial), with no apparent geographic or host species pattern, suggestive of multiple introductions. The availability of additional mitochondrial gene sequences also enabled a re-evaluation of a range of putative molecular markers of S. scabiei, revealing that cox1 is the most informative gene for molecular epidemiological investigations. Utilising this gene target, we provide additional evidence to support cross-host transmission between different animal hosts. CONCLUSIONS: Our results suggest a history of parasite invasion through colonisation of Australia from hosts across the globe and the potential for cross-host transmission being a common feature of the epidemiology of this neglected pathogen. If this is the case, comparable patterns may exist elsewhere in the 'New World'. This work provides a basis for expanded molecular studies into mange epidemiology in humans and animals in Australia and other geographic regions.

Urban landscapes can change virus gene flow and evolution in a fragmentation-sensitive carnivore.

Urban expansion has widespread impacts on wildlife species globally, including the transmission and emergence of infectious diseases. However, there is almost no information about how urban landscapes shape transmission dynamics in wildlife. Using an innovative phylodynamic approach combining host and pathogen molecular data with landscape characteristics and host traits, we untangle the complex factors that drive transmission networks of feline immunodeficiency virus (FIV) in bobcats (Lynx rufus). We found that the urban landscape played a significant role in shaping FIV transmission. Even though bobcats were often trapped within the urban matrix, FIV transmission events were more likely to occur in areas with more natural habitat elements. Urban fragmentation also resulted in lower rates of pathogen evolution, possibly owing to a narrower range of host genotypes in the fragmented area. Combined, our findings show that urban landscapes can have impacts on a pathogen and its evolution in a carnivore living in one of the most fragmented and urban systems in North America. The analytical approach used here can be broadly applied to other host-pathogen systems, including humans.

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIVPle ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIVPle molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIVPle co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIVPle network. While social organization (i.e., pride) was an important component of FIVPle transmission pathways at all scales, we find that FIVPle subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIVPle transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects.